Generative AI Is Quietly Rewriting the Underlying Logic of China's Cross-Border Trade

A while ago, I had dinner with a friend who has been in foreign trade for more than a decade.

He used to be the classic factory owner. Steady orders, steady clients, steady margins. His big customers would place two orders a year, tens of thousands of units each — he could schedule production in his sleep.

But that night, holding his glass, he said something that stopped me cold.

He said, "Liu Run, I can't sleep these nights."

Why?

Because his biggest client didn't place an order this year.

A Migration Everyone Can Feel

He's not an isolated case.

Over the past five years, China's cross-border e-commerce trade has grown tenfold. Tenfold. Think about what that means.

In 2023, China's total imports and exports reached 41.76 trillion yuan. Of that, cross-border e-commerce imports and exports already accounted for 2.38 trillion yuan, up 15.6% year on year. Exports alone hit 1.83 trillion yuan, climbing nearly 20%.

Behind this is a vast new ecosystem. As of 2024, China has more than 120,000 cross-border e-commerce entities, over 200,000 standalone （direct-to-consumer online stores） sites, more than 1,000 cross-border e-commerce industrial parks, and overseas warehouse space exceeding 30 million square meters.

And there's one number that stands out even more.

Research firms estimate that over 40% of the sellers on Amazon come from China.

What does that tell you?

It tells you that a large wave of factories — outfits that once only knew how to take big orders and produce to spec — are collectively "going overseas" （a Chinese business term for expanding into overseas markets）. They're no longer serving just one or two big clients. They're selling directly into the shopping carts of overseas consumers.

This isn't a tweak. This is switching to a whole new track.

And what's pushing them forward, beyond margin pressure, is something new.

Generative AI.

A Tool That Collapsed the Barrier

What is generative AI?

Plainly put, it's the kind of tool where you give it a sentence, and it writes you a paragraph, generates an image, or produces a video.

You may have used it, or you may have only heard of it. But for cross-border e-commerce sellers, this thing has been in their hands for a while.

Here's a data point: on Alibaba.com （Alibaba's B2B cross-border e-commerce marketplace） alone, more than 100 million product listings are generated by generative AI. Merchants can call on AI tools across more than 40 e-commerce scenarios.

Writing product descriptions, building detail-page images, replying to customer emails, analyzing inventory, recommending products. AI can insert itself into almost every link of the selling chain.

And it's cheap.

It used to be that a cross-border seller had to keep copywriters, designers, and customer service on staff — a whole team. Now, one operator （a distinct e-commerce role covering listings, ads, and customers） who knows how to ask the right questions, plus a few AI tools, can get all of that done.

Crazy.

The barrier has collapsed. People who can write Chinese can now do business overseas too.

Sounds like all good news, right?

But there's always a flip side.

Pitfall One: What Everyone Writes Comes Out Looking the Same

My friend complained to me about this.

He lists the same product across Amazon, his standalone site, and TikTok at the same time. To be efficient, he had his team use the same AI tool to write copy for the same product on different platforms.

The result?

What came out was almost identical.

Why?

Because everyone is using the same kind of model, fed the same kind of data, and even the prompts are copied from the internet. The "reference answers" inside the AI are more or less the same, so of course what it spits out is more or less the same.

The consequences are serious.

A consumer opens pages from two different brands and finds descriptions, selling points, even the tone of voice looking like one person wrote them all. They can't tell who is who. When they can't tell, they're not loyal. When they're not loyal, they don't buy.

Livestreaming is even more of a problem. If livestream scripts are also AI-generated, then competitors end up delivering the same pitch.

Homogenization is quietly eating away at these sellers' differentiation.

Pitfall Two: There Aren't Nearly Enough People Who Know How to Use It

Just how many AI tools are out there?

Every few weeks, a new one pops up on the market. Features update fast, the variety is huge, and even specialists can't keep track of them all.

For a small or medium-sized enterprise, what does that mean?

It means no one can use them well.

Cross-border e-commerce was already short on talent. Operations, ad placement, data analysis — these roles were already hard to fill. And now you also need these people to understand AI, know how to use AI, and judge whether what AI produces is reliable.

It's just too hard.

ChatGPT came out in 2022; Alibaba.com's AI tools only launched in 2023. Many SME owners still haven't figured out how to use this thing themselves, let alone teach their employees or manage their teams around it.

The result: a pile of tools bought, and very few actually in use.

Pitfall Three: It Sounds Convincing, but You Have No Idea If It's Right

This is the most hidden pitfall of all.

AI-generated content looks professional. The grammar is smooth, the logic is clear, there's even data. But is it right?

Nobody knows.

A lot of SMEs simply don't have the ability to verify it. They don't have enough samples in hand, no baseline for comparison, and no one dedicated to fact-checking. Taking AI's marketing advice out to market to test and learn is costly, slow, and often not even affordable.

What's more, the people using AI are mostly junior and mid-level operators, not senior people. The senior people are, if anything, more cautious. Which means the very people most likely to take AI's output at face value are precisely the ones least equipped to judge it.

That gap is the risk.

Pitfall Four: What You Feed It May Be Leaking

This last pitfall is the easiest to overlook.

You use AI to analyze customer data, enter product specs, organize marketing strategies. The moment you type these things in, they leave your computer.

And what if, among that information, there's your customer list, your new product design, your pricing strategy?

Once it leaks into the hands of competitors, the consequences are hard to imagine.

As of April 2024, 117 large models in China had completed regulatory filing （China's filing system for AI services）. The AI tools on the market are a mixed bag, varying wildly in quality. The same operator might use one today and another tomorrow — and every use adds one more chance for data to leak.

This isn't fear-mongering. This is a quiet, everyday risk happening right now.

So What Do You Do?

I've laid out all these pitfalls not to tell you to avoid AI.

Quite the opposite. With AI, if you don't use it and others do, you'll be the one eliminated.

The key is: how to use it right.

Let me give you a few practical suggestions.

First, learn before you buy.

Don't rush to pay for premium tools. Platforms like Amazon and Alibaba.com already offer free AI tools and online courses. For companies that haven't yet gotten started, that's the best entry point. Let your employees get fluent with the free tools first, integrate AI into their own business scenarios, and only then consider paying.

Second, build a verification mechanism.

What AI gives you can't go straight into production. It needs verification. How? Use the platform's big data. Big data is good at capturing consumers' real behavior — what they clicked, how long they looked, what they bought. Use that real data to reverse-engineer whether AI's marketing advice actually works. At the same time, talk more with overseas buyers and hear their honest take on your marketing content. They're the truest touchstone.

Third, find partners. Don't go it alone.

SMEs have limited resources; one person can't carry the whole AI effort alone. Go find platforms, technology service providers, peers — and build an ecosystem together. Go to the meet-ups organized by industry associations, the skills competitions hosted by platforms. Share experience, share costs.

Fourth, give AI a "job description."

AI can do a lot, but it isn't omnipotent. You have to be clear which work you hand to it, and which work must be done by people. For example, generated scripts should be polished by a human, to ensure diversity and quality of content. Treat AI as a "virtual employee" — give it responsibilities, give it boundaries. Its capabilities are changing, and your evaluation has to change with them.

Fifth, build compliance into your core.

Before you use AI, do a legal and compliance assessment first. China has already issued the Interim Measures for the Management of Generative Artificial Intelligence Services （《生成式人工智能服务管理暂行办法》）, with clear requirements on privacy protection, intellectual property, and fair competition. Before using a tool, confirm whether it has completed its regulatory filing. If necessary, have a specialized lawyer do regular risk assessments. This is not money you can afford to save.

A Closing Note

So what happened to my foreign-trade friend?

He didn't give up on AI. But he's no longer a blind believer in it either.

He had his team practice on free tools first, and once a week they'd review what was AI-generated and how it performed. He formed a small circle with a few peers to regularly share the traps they'd hit. He also brought in a lawyer to walk through the entire data-usage process.

Half a year later, he told me his team's efficiency had genuinely improved. More importantly, he was finally sleeping well again.

Generative AI is rewriting the underlying logic of cross-border trade. This has already happened — it isn't still happening.

But no matter how powerful the tool, it's still just a tool. What truly determines how far you'll go is always how you use it.

May you, in this wave, stay free of anxiety, refuse to follow the herd, use it with a steady hand, and go far.